aliyun-qwen-coder
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npx mdskill add cinience/alicloud-skills/aliyun-qwen-coderGenerates and understands code using Alibaba Cloud Qwen Coder models
- Solves code generation, repository analysis, and coding-agent tasks
- Depends on Alibaba Cloud Model Studio and DashScope SDK
- Chooses appropriate coder models based on task complexity and requirements
- Delivers results via prompts, summaries, and structured payloads in output directory
SKILL.md
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--- name: aliyun-qwen-coder description: Use when code generation, repository understanding, or coding-agent tasks need Alibaba Cloud Model Studio Qwen Coder models (`qwen3-coder-next`, `qwen3-coder-plus` and related coder variants). version: 1.0.0 --- Category: provider # Model Studio Qwen Coder ## Validation ```bash mkdir -p output/aliyun-qwen-coder python -m py_compile skills/ai/code/aliyun-qwen-coder/scripts/prepare_code_request.py && echo "py_compile_ok" > output/aliyun-qwen-coder/validate.txt ``` Pass criteria: command exits 0 and `output/aliyun-qwen-coder/validate.txt` is generated. ## Output And Evidence - Save prompts, repository context summaries, and normalized coding request payloads under `output/aliyun-qwen-coder/`. - Record the exact model, endpoint mode, and target language/framework for reproducibility. Use Qwen Coder for coding assistants, code review drafting, repository-level reasoning, patch planning, and tool-using software agents. ## Critical model names Use one of these exact model strings as appropriate: - `qwen3-coder-next` - `qwen3-coder-plus` - `qwen-coder-plus` - `qwen2.5-coder-32b-instruct` ## Prerequisites - Install SDK in a virtual environment: ```bash python3 -m venv .venv . .venv/bin/activate python -m pip install dashscope ``` - Set `DASHSCOPE_API_KEY` in your environment, or add `dashscope_api_key` to `~/.alibabacloud/credentials`. - Prefer the OpenAI-compatible endpoint when a client does not yet expose the latest coder models in dropdown UI. ## Normalized interface (code.generate) ### Request - `messages` (array<object>, required) - `model` (string, optional): default `qwen3-coder-next` - `repository_summary` (string, optional) - `files` (array<string>, optional) - `language` (string, optional) - `tools` (array<object>, optional) - `stream` (bool, optional) ### Response - `text` (string) - `patch` (string, optional) - `usage` (object, optional) ## Quick start ```bash python skills/ai/code/aliyun-qwen-coder/scripts/prepare_code_request.py \ --task "Refactor request validation into a small helper and add one unit test." \ --language python ``` ## Operational guidance - Pass only the files relevant to the requested change to reduce noise. - Use `qwen3-coder-next` for current-generation coding tasks and `qwen3-coder-plus` when you need a stronger but potentially costlier coder. - For repo-scale changes, include architecture notes and expected test commands. - Prefer deterministic prompts and pinned model IDs for benchmarking or regression comparison. ## Output location - Default output: `output/aliyun-qwen-coder/requests/` - Override base dir with `OUTPUT_DIR`. ## References - `references/sources.md`